CN114079668B - Information acquisition and arrangement method and system based on internet big data - Google Patents
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Abstract
The invention relates to an information acquisition and arrangement method and system based on internet big data, wherein the system needs to be built before the system works. At least two or more client sides are arranged, a source end data acquisition end is embedded in each client side, and a data preprocessing module is embedded in the source end data acquisition end; setting a data server, configuring the data server to have a data server cache end and a shared cache end, and then establishing communication connection between the client and the data server. The communication connection between the client and the data server adopts a communication wake-up and use mode; namely, the data preprocessing module wakes up the connection between the communication channel and the data server through the synchronous task processing thread. The target data can be traced, all the target data are cached and stored in a sharing mode, the storage capacity is strong, the data can be modified at any time, the demand response to the data change is more timely, and the global flexibility is realized.
Description
Technical Field
The invention relates to the technical field of internet big data, in particular to an information acquisition and arrangement method and system based on internet big data.
Background
The traditional informatization construction basically takes business as guidance, and the original manual process is automated and efficient by using a computer technology. The information systems are often integrated by application programs and corresponding database systems, which are not communicated with each other, and gradually form enterprise data islands.
With the increasingly updated internet of things and the continuous excavation of big data, in some fields, data exchange and fusion between data islands are started to be realized, so that more data opinions which can be referred to are provided for different enterprises, when data excavation is carried out, a tracking system between an acquisition end and a storage end is often required to be established so as to be capable of carrying out retrieval analysis on data of different ends, at present, when new business is required, one-time data extraction is carried out from each source system, and a series of complicated steps such as department coordination, system account opening, data dictionaries and the like are involved. And common tools are based on a batch periodic drawing mode, some service scenes with high real-time requirements on data are difficult to realize, reusability is avoided, and a large amount of manpower is needed to be spent on resynchronization or a synchronization program is needed to be modified to realize each time a new requirement or a requirement is changed.
Disclosure of Invention
In view of the above, the present invention provides an information collecting and organizing method and system based on internet big data to solve the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme:
the information acquisition and arrangement method based on the internet big data comprises the following steps:
when new data are generated at different source ends, a data preprocessing module embedded in the source end writes the new data in a first attribute value of the source end;
the data server captures the new data by using the synchronous data acquisition unit and taking the timestamp as a mark, and transmits the new data to a cache end of the data server;
establishing a plurality of task chains at the cache end of the data server, and establishing a mapping table between the task chains and the source end, so that one source end corresponds to one task chain;
the task chain extracts new data corresponding to a cache end of the data server according to a timestamp, when a new segment of new data is extracted by the task chain, a new record is correspondingly generated and sent to a processing link, the processing link calls the new data in the task chain according to the new record, the new data is filtered in a processing module, the new data with empty content is filtered, then the new data is converted into structured data to form target data, the target data is stored in a data cache layer of a sharing end, a link mark is formed on the sharing end, and the link mark is used for verifying the target data of the data cache layer.
Further, when new data is generated at the source end, a new data generation event is acquired through a trigger built in the source end, the new data generation event triggers a data preprocessing module to call the new data from a database of the source end and read a first attribute value of the source end at the same time, and the data preprocessing module takes the first attribute value of the source end and the time of new data generation as a second attribute value of the new data; meanwhile, the data preprocessing module wakes up the connection between the communication channel and the data server through the synchronous task processing thread.
Furthermore, after the connection between the data server and the communication channel is awakened, the new data with the second attribute value is captured by taking the timestamp as a mark according to the synchronous task processing thread and is transmitted to the cache end of the data server.
Further, the link identifier is used to verify target data of the data cache layer, and specifically includes:
after the link identification starts a check task, target data is inquired according to the link identification and new data generated by the corresponding source end, and a database of the source end and a data cache layer of the sharing end are traversed simultaneously by a method of reading and comparing at the same time to check the consistency of the data link.
The invention also provides an information acquisition and arrangement system based on the internet big data, which comprises the following components:
the method comprises the following steps that a plurality of clients are used as a source end, and when new data are generated at the source end, a data preprocessing module embedded in the source end writes the new data by using a first attribute value of the source end as a reference value for new data attribute writing;
the data server is connected with the client and comprises a plurality of synchronous data collectors and a data server cache end;
the data server cache end is provided with a plurality of task chains established according to the client, a processing link formed based on the task chains and a processing module, and the data server also comprises a sharing end corresponding to the data server cache end;
the data server captures the new data by using a synchronous data acquisition unit and taking a timestamp as a mark, and transmits the new data to a cache end of the data server;
the task chain extracts new data corresponding to the cache end of the data server according to the time stamp, when a new segment of new data is extracted by the task chain, a new record is correspondingly generated and sent to the processing link, the processing link calls the new data in the task chain according to the new record, the new data is filtered and converted in the processing module to form target data, and the target data is stored in the data cache layer of the sharing end.
Furthermore, the processing module is provided with a filtering unit and a conversion unit;
the filtering unit is used for filtering new data with empty content;
the conversion unit is used for converting the new data which is filtered by the filtering unit into structured data to form target data.
Further, after target data are stored, the sharing end forms a link identifier based on the target data, and the link identifier is used for verifying the target data of the data cache layer.
Furthermore, the data preprocessing module calls the new data from the database of the client and reads the first attribute value of the source end at the same time, and the data preprocessing module takes the first attribute value of the source end and the time generated by the new data as the second attribute value of the new data; meanwhile, the data preprocessing module wakes up the connection between the communication channel and the data server through the synchronous task processing thread.
Furthermore, the data server captures the new data with the second attribute value by taking the timestamp as a mark according to the synchronous task processing thread and transmits the captured new data to the cache end of the data server.
Further, the link identifier is used for querying the target data according to the link identifier and the new data generated by the corresponding source end, and the database of the source end and the data cache layer of the sharing end are traversed simultaneously by a method of reading and comparing at the same time to check the consistency of the data link.
When different clients generate new data, the new data is marked so as to be convenient for tracing, in the whole process, a task chain can also form a corresponding new record when extracting the new data, a processing link calls the new data in the task chain according to the new record, the new data is filtered and converted in a processing module to form target data and the target data is stored in a data cache layer of a sharing end, a corresponding link identification is generated, the link identification is used for inquiring the target data according to the link identification and the corresponding new data generated by the source end, and a method for reading and comparing is used for traversing a database of the source end and the data cache layer of the sharing end simultaneously to carry out data link consistency check.
In the above, when new data is generated at the source end, a new data generation event is acquired through a trigger built in the source end, the new data generation event triggers a data preprocessing module to retrieve the new data from a database of the source end and simultaneously read a first attribute value of the source end, the data preprocessing module takes the first attribute value of the source end and the time of new data generation as a second attribute value of the new data, and meanwhile, the data preprocessing module wakes up connection between a communication channel and a data server through a synchronous task processing thread. Therefore, the invention can automatically capture data, and uniformly arrange and store the data only by linking and communicating the client and the data server, thereby facilitating the back-end analysis to capture the data.
In the above, the big data information collecting and sorting system provided by the invention does not need human intervention, and the new data can be captured by the synchronous data collector with the timestamp as a mark and transmitted to the data server cache end, so as to obtain real-time data and analyze timeliness of data use.
In the above, the target data can be traced, and all the target data are cached and stored in a shared manner, so that the storage capacity is strong, the modification at any time is supported, and the demand response to the data change is more timely and has global flexibility.
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FIG. 1 is a schematic diagram of the framework of the present invention;
fig. 2 is a schematic diagram of a framework in an embodiment of the invention.
Detailed Description
The present invention is described in detail below with reference to the accompanying drawings, which refer to fig. 1 to 2.
The invention provides an information acquisition and arrangement method based on internet big data, which specifically comprises the following steps:
when the source end has new data generation, a data preprocessing module embedded in the source end writes the new data by using a first attribute value of the source end; specifically, when new data is generated at the source end, a new data generation event is acquired through a trigger built in the source end, the new data generation event triggers a data preprocessing module to call the new data from a database of the source end and read a first attribute value of the source end at the same time, and the data preprocessing module takes the first attribute value of the source end and the time of new data generation as a second attribute value of the new data; meanwhile, the data preprocessing module wakes up the connection between the communication channel and the data server through a synchronous task processing thread;
and when the connection between the data server and the communication channel is awakened, capturing the new data with the second attribute value by taking the timestamp as a mark according to the synchronous task processing thread, and transmitting the captured new data to a cache end of the data server.
Establishing a plurality of task chains at the cache end of the data server, and establishing a mapping table between the task chains and the source end, so that one source end corresponds to one task chain;
the method includes the steps that a task chain extracts new data corresponding to a cache end of a data server according to a timestamp, when each new data is extracted by the task chain, a new record is correspondingly generated and sent to a processing link, the processing link calls the new data in the task chain according to the new record, the new data is filtered in a processing module, the new data with empty content is filtered, then the new data is converted into structured data to form target data, the target data is stored in a data cache layer of a sharing end, a link mark is formed on the sharing end, and the link mark is used for verifying the target data of the data cache layer, and specifically includes the following steps:
after the link identification starts a check task, target data is inquired according to the link identification and new data generated by the corresponding source end, and a database of the source end and a data cache layer of the sharing end are traversed simultaneously by a method of reading and comparing at the same time to check the consistency of the data link.
In order to facilitate the implementation of the method, the application provides an information acquisition and arrangement system based on internet big data, which comprises the following steps:
the method comprises the following steps that a plurality of clients are used as a source end, and when new data are generated at the source end, a data preprocessing module embedded in the source end writes the new data by using a first attribute value of the source end as a reference value for new data attribute writing; specifically, the data preprocessing module calls the new data from the database of the client and reads a first attribute value of the source end at the same time, and the data preprocessing module takes the first attribute value of the source end and the time generated by the new data as a second attribute value of the new data; meanwhile, the data preprocessing module wakes up the connection between the communication channel and the data server through the synchronous task processing thread.
In the above, when new data is generated at the source end, a new data generation event is acquired through a trigger built in the source end, the new data generation event triggers a data preprocessing module to retrieve the new data from a database of the source end and simultaneously read a first attribute value of the source end, the data preprocessing module takes the first attribute value of the source end and the time of new data generation as a second attribute value of the new data, and meanwhile, the data preprocessing module wakes up connection between a communication channel and a data server through a synchronous task processing thread. Therefore, the invention can automatically capture data, and uniformly arrange and store the data only by linking and communicating the client and the data server, thereby facilitating the back-end analysis to capture the data.
The data server is connected with the client and comprises a plurality of synchronous data collectors and a data server cache end; specifically, the data server captures the new data with the second attribute value by using the timestamp as a mark according to the synchronous task processing thread and transmits the captured new data to the cache end of the data server. The big data information acquisition and arrangement system provided by the invention does not need human intervention, and can capture the new data by taking the timestamp as a mark through the synchronous data acquisition unit and transmit the captured new data to the cache end of the data server so as to acquire real-time data and analyze the timeliness of data use.
In the above, the data server cache end has a plurality of task chains established according to the client, a processing link formed based on the task chains, and a processing module, and the data server further includes a sharing end corresponding to the data server cache end;
the data server captures the new data by using a synchronous data acquisition unit and taking a timestamp as a mark, and transmits the new data to a cache end of the data server;
the task chain extracts new data corresponding to the cache end of the data server according to the time stamp, when a new segment of new data is extracted by the task chain, a new record is correspondingly generated and sent to the processing link, the processing link calls the new data in the task chain according to the new record, the new data is filtered and converted in the processing module to form target data, and the target data is stored in the data cache layer of the sharing end.
In the above, the processing module has a filtering unit and a converting unit;
the filtering unit is used for filtering new data with empty content;
the conversion unit is used for converting the new data which is filtered by the filtering unit into structured data to form target data.
In the above, after the target data is stored, the sharing end forms a link identifier based on the target data, and the link identifier is used for verifying the target data of the data cache layer. When different clients generate new data, the new data is marked so as to be convenient for tracing, in the whole process, a task chain can also form a corresponding new record when extracting the new data, a processing link calls the new data in the task chain according to the new record, the new data is filtered and converted in a processing module to form target data and the target data is stored in a data cache layer of a sharing end, a corresponding link identification is generated, the link identification is used for inquiring the target data according to the link identification and the corresponding new data generated by the source end, and a method for reading and comparing is used for traversing a database of the source end and the data cache layer of the sharing end simultaneously to carry out data link consistency check.
Through the data link consistency check, the target data can be traced, all the target data are cached and stored in a sharing mode, the storage capacity is strong, the data can be modified at any time, the data change demand response is timely, and the global flexibility is realized.
The specific principle is as follows: the invention provides an information acquisition and arrangement system based on internet big data, which needs to be built before the system works.
At least two or more client sides are arranged, a source end data acquisition end is embedded in each client side, and a data preprocessing module is embedded in the source end data acquisition end;
setting a data server, configuring the data server to have a data server cache end and a shared cache end, and then establishing communication connection between the client and the data server.
The communication connection between the client and the data server adopts a communication wake-up and use mode; namely, the data preprocessing module wakes up the connection between the communication channel and the data server through the synchronous task processing thread.
After the construction is completed, when new data is generated at the source end, the data preprocessing module embedded in the source end writes the new data into the source end according to the first attribute value of the source end; specifically, when new data is generated at the source end, a new data generation event is acquired through a trigger built in the source end, the new data generation event triggers a data preprocessing module to call the new data from a database of the source end and read a first attribute value of the source end at the same time, and the data preprocessing module takes the first attribute value of the source end and the time of new data generation as a second attribute value of the new data; meanwhile, the data preprocessing module wakes up the connection between the communication channel and the data server through a synchronous task processing thread;
and when the connection between the data server and the communication channel is awakened, capturing the new data with the second attribute value by taking the timestamp as a mark according to the synchronous task processing thread, and transmitting the captured new data to a cache end of the data server.
Establishing a plurality of task chains at the cache end of the data server, and establishing a mapping table between the task chains and the source end, so that one source end corresponds to one task chain;
the method includes the steps that a task chain extracts new data corresponding to a cache end of a data server according to a timestamp, when each new data is extracted by the task chain, a new record is correspondingly generated and sent to a processing link, the processing link calls the new data in the task chain according to the new record, the new data is filtered in a processing module, the new data with empty content is filtered, then the new data is converted into structured data to form target data, the target data is stored in a data cache layer of a sharing end, a link mark is formed on the sharing end, and the link mark is used for verifying the target data of the data cache layer, and specifically includes the following steps:
after the link identification starts a check task, target data is inquired according to the link identification and new data generated by the corresponding source end, and a database of the source end and a data cache layer of the sharing end are traversed simultaneously by a method of reading and comparing at the same time to check the consistency of the data link.
The principles and embodiments of the present invention are explained herein using specific examples, which are presented only to assist in understanding the method and its core concepts of the present invention. The foregoing is only a preferred embodiment of the present invention, and it should be noted that there are objectively infinite specific structures due to the limited character expressions, and it will be apparent to those skilled in the art that a plurality of modifications, decorations or changes may be made without departing from the principle of the present invention, and the technical features described above may be combined in a suitable manner; such modifications, variations, combinations, or adaptations of the invention using its spirit and scope, as defined by the claims, may be directed to other uses and embodiments.
Claims (10)
1. The information acquisition and arrangement method based on the internet big data is characterized by comprising the following steps:
when new data are generated at different source ends, a data preprocessing module embedded in the source end writes the new data by using a first attribute value of the source end to obtain the new data endowed with the first attribute value;
the data server captures the new data endowed with the first attribute value by using a synchronous data acquisition unit by taking a timestamp as a mark and transmits the captured new data to a cache end of the data server;
establishing a plurality of task chains at the cache end of the data server, and establishing a mapping table between the task chains and the source end, so that one source end corresponds to one task chain;
the task chain extracts new data which are corresponding to a cache end of a data server and are endowed with a first attribute value according to a timestamp, when each section of new data is extracted by the task chain, a new record is correspondingly generated and sent to a processing link, the processing link calls the new data in the task chain according to the new record, the new data is filtered in a processing module, the new data with empty content is filtered, then the new data is converted into structured data to form target data, the target data is stored in a data cache layer of a sharing end, a link identification is formed on the sharing end, and the link identification is used for verifying the target data of the data cache layer.
2. The method for collecting and arranging information based on internet big data according to claim 1, wherein when new data is generated at the source end, a new data generation event is obtained through a trigger built in the source end, the new data generation event triggers a data preprocessing module to call the new data from a database of the source end and read a first attribute value of the source end at the same time, and the data preprocessing module takes the first attribute value of the source end and the time of generating the new data as a second attribute value of the new data; meanwhile, the data preprocessing module wakes up the connection between the communication channel and the data server through the synchronous task processing thread.
3. The method for collecting and organizing information based on internet big data according to claim 1 or 2, wherein after the connection between the data server and the communication channel is awakened, the new data with the second attribute value is captured by taking a timestamp as a mark according to a synchronous task processing thread and is transmitted to a cache end of the data server.
4. The method for collecting and organizing information based on internet big data according to claim 1, wherein the link identifier is used for verifying target data of a data cache layer, and specifically comprises:
after the link identification starts a check task, target data is inquired according to the link identification and new data generated by the corresponding source end, and a database of the source end and a data cache layer of the sharing end are traversed simultaneously by a method of reading and comparing at the same time to check the consistency of the data link.
5. Information acquisition arrangement system based on internet big data, its characterized in that includes:
the method comprises the steps that a plurality of clients are used as a source end, and when new data are generated at the source end, a data preprocessing module embedded in the source end writes the new data with a first attribute value of the source end to obtain the new data endowed with the first attribute value;
the data server is connected with the client and comprises a plurality of synchronous data collectors and a data server cache end;
the data server cache end is provided with a plurality of task chains established according to the client, a processing link formed based on the task chains and a processing module, and the data server also comprises a sharing end corresponding to the data server cache end;
the data server captures the new data endowed with the first attribute value by using a synchronous data acquisition unit by taking a timestamp as a mark and transmits the captured new data to a cache end of the data server;
the task chain extracts new data which are corresponding to the cache end of the data server and are endowed with a first attribute value according to the time stamp, when each section of new data is extracted by the task chain, a new record is correspondingly generated and sent to the processing link, the processing link calls the new data in the task chain according to the new record, the new data are filtered and converted in the processing module to form target data, and the target data are stored in the data cache layer of the sharing end.
6. The internet big data based information acquisition and arrangement system according to claim 5, wherein the processing module has a filtering unit and a converting unit;
the filtering unit is used for filtering new data with empty content;
the conversion unit is used for converting the new data which is filtered by the filtering unit into structured data to form target data.
7. The system as claimed in claim 5, wherein the sharing end forms a link identifier based on the target data after the target data is stored, and the link identifier is used for verifying the target data of the data caching layer.
8. The system according to claim 5, wherein the data preprocessing module retrieves the new data from the database of the client and reads the first attribute value of the source, and the data preprocessing module takes the first attribute value of the source and the time of the new data generation as the second attribute value of the new data; meanwhile, the data preprocessing module wakes up the connection between the communication channel and the data server through the synchronous task processing thread.
9. The system for collecting and organizing information based on internet big data according to claim 5, wherein the data server captures the new data with the second attribute value by taking a timestamp as a mark according to a synchronous task processing thread and transmits the new data to a data server cache.
10. The system of claim 7, wherein the link identifier is configured to query target data according to the link identifier and new data generated by the source end, and perform data link consistency check by traversing a database of the source end and a data cache layer of the sharing end simultaneously by a method of reading and comparing.
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